Many systems use large-scale machine learning to accomplish challenging problems such as speech recognition, computer vision, image and sound file searching and categorization, etc. Deep learning of multi-layer neural networks is an effective large-scale approach. Kernel methods, e.g., Gaussian and polynomial kernels, have also been used on smaller-scale problems, but scaling kernel methods has proven challenging.